Distributed network control for mobile multi-modal wireless sensor networks

A sensor network operates on an infrastructure of sensing, computation, and communication, through which it perceives the evolution of events it observes. We propose a fusion-driven distributed dynamic network controller, called MDSTC, for a multi-modal sensor network that incorporates distributed computation for in-situ assessment, prognosis, and optimal reorganization of constrained resources to achieve high quality multi-modal data fusion. For arbitrarily deployed sensors, a certain level of data quality cannot be guaranteed in sparse regions. MDSTC reallocates resources to sparse regions; reallocation of network resources in this manner is motivated by the fact that an increased density of sensor nodes in a region of interest leads to better quality data and enriches the network resilience. Simulation results in NS-2 show the effectiveness of the proposed MDSTC. 1

Research highlights
► A software module called MDSTC that resides at every sensor node in the network and is independent of the sensor type.
► A novel multicast group management protocol that handles multicast groups between same-modality and complementary modality sensors.
► A sensor mobility based protocol for re-allocating resources to sparse regions, regions in which sensors of certain modality are missing.
► Two methods for partitioning a circular region of interest into desired regions (Concentric Circles and Circular Sectors).
► A Greedy algorithm for sensor placement and coverage that selects nodes from the available ones for each of the regions (Algorithm Choose-1-out-of-M).
► NS-2 simulations that validate and verify the effectiveness of the proposed MDSTC.